• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.688-698
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• 2012

This paper deals with ROLSO (Reduced Order Luenberger State Observer) design to prevent jackknifing phenomenon of articulated vehicles consisting of the tractor and semi-trailer by using GPS. In addition, by applying the regulator system using ROLSO feedback system, simulation's result presents that articulated vehicle's states are stabilized than the human's PR time (Preception Response time) rapidly. This simulation verifies that the automatic control of articulated vehicle's can be applied for the accident prevention for the time that the driver is unable to manage with the sudden accident. For this simulation, by using the equation of planar motion, the modeling of the articulated vehicle was performed. This modeling was expressed in the state space model. And FOLSO (Full Order Luenberger State Observer), ROLSO were designed by using the state space model of an articulated vehicle's dynamics.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.1-1
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• 2003

In this talk, a reduced-order modeling methodology based on centroidal Voronoi tessellations (CVT's)is introduced. CVT's are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi cells. The discrete data sets, CVT's are closely related to the h-means clustering techniques. Even with the use of good mesh generators, discretization schemes, and solution algorithms, the computational simulation of complex, turbulent, or chaotic systems still remains a formidable endeavor. For example, typical finite element codes may require many thousands of degrees of freedom for the accurate simulation of fluid flows. The situation is even worse for optimization problems for which multiple solutions of the complex state system are usually required or in feedback control problems for which real-time solutions of the complex state system are needed. There hava been many studies devoted to the development, testing, and use of reduced-order models for complex systems such as unsteady fluid flows. The types of reduced-ordered models that we study are those attempt to determine accurate approximate solutions of a complex system using very few degrees of freedom. To do so, such models have to use basis functions that are in some way intimately connected to the problem being approximated. Once a very low-dimensional reduced basis has been determined, one can employ it to solve the complex system by applying, e.g., a Galerkin method. In general, reduced bases are globally supported so that the discrete systems are dense; however, if the reduced basis is of very low dimension, one does not care about the lack of sparsity in the discrete system. A discussion of reduced-ordering modeling for complex systems such as fluid flows is given to provide a context for the application of reduced-order bases. Then, detailed descriptions of CVT-based reduced-order bases and how they can be constructed of complex systems are given. Subsequently, some concrete incompressible flow examples are used to illustrate the construction and use of CVT-based reduced-order bases. The CVT-based reduced-order modeling methodology is shown to be effective for these examples and is also shown to be inexpensive to apply compared to other reduced-order methods.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.50.2-50
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• 2002

1. Introduction 2. Reduced-Order Model of Robot System 3. Model-Based Control 4. Simulation Results 5. Experimental Results and Considerations 6. Conclusions

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.5
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• pp.336-343
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• 2008

This paper proposes a novel sensorless control scheme for a Permanent Magnet Synchronous Motor (PMSM) by using a parallel reduced-order Extended Kalman Filter. The proposed scheme can obtain rotor position and speed by back-EKF that is estimated by reduced-order ETD and save computation time great)y due to using a parallel structure that works by turns every sampling time. Therefore, proposed scheme has merits of conventional EKF, and problems of parameter sensitivity are partially overcome. And proposed scheme can safely estimate rotor speed and position by using new algorithms according to driving regions. Experimental results show the validity of the proposed estimation technique, and to verify the merit of the proposed scheme, a comparison of a new reduced-order EKF algorithm with a conventional EKF algorithm has been also made in terms of computation time.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.485-488
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• 1999

In this paper, a current control system for single phase PWM AC/DC converter without the source voltage sensors is proposed. The sinusoidal input current and unity effective power factor are realised based on the estimated source voltage in the controller. The estimation of source voltage is performed by the reduced-order Luenberger observer using actual currents. The estimated source voltage is used to accomplish unity power factor. The proposed method is proved by experiments.

• Proceedings of the KIPE Conference
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• 1998.11a
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• pp.78-82
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• 1998

In this paper, the authors propose a current control system of single phase PWM AC/DC converter without the source voltage sensors. The sinusoidal input current and unity effective power factor are realised based on the estimated source voltage in the controller. The estimations of source voltage are performed based on the reduced-order Luenberger observer using actual currents. The estimated source voltage is used to accomplish unity power factor. The proposed method is proved by simulations

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.240-245
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• 1990

A on-line optimization scheme based on model in a binary distillation process is proposed. A reduced-order model utilized the concept of collocation is used as a process model and the recursive prediction error method is employed to identify the reduced-order model. The concentrations of end products are controlled by nonlinear adaptive predictive control algorithm. The objective function is constructed to find optimum operate condition for saving utility cost. The proposed optimization is scheme is tested through simulation studies in 13-staged water-methanol distillation column.

• Journal of Mechanical Science and Technology
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• v.16 no.12
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• pp.1643-1651
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• 2002

Magnetic levitation systems are required to have a large operating range in many applications. As one method to solve this problem, Time Delay Control (TDC) is applied to a single-axis magnetic levitation system in this paper A reduced-order observer is utilized to estimate states excluding measurable states in the control law. The system consists of a square air-core solenoid and a circular permanent magnet attached on a plastic ball. Theoretical magnetic forces of the system are obtained on the basis of the location of the magnet around the solenoid. The magnetic levitation force is obtained by the experiment, and then compared with the theoretical one. As the results of the control experiments, the nonlinear controller (TDC : 1-2 ㎜) has a larger operating range than the linear controller (PD control : 1-1.4 ㎜), and is superior to linear. control in the robustness to the modeling uncertainty and the performance of the disturbance rejection.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.1-9
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• 2006

This paper presents the modeling and multivariable feedback control of a novel high-precision multi-dimensional positioning stage. This integrated 6-degree-of-freedom. (DOF) motion stage is levitated by three aerostatic bearings and actuated by 3 three-phase synchronous permanent-magnet planar motors (SPMPMs). It can generate all 6-DOF motions with only a single moving part. With the DQ decomposition theory, this positioning stage is modeled as a multi-input multi-output (MIMO) electromechanical system with six inputs (currents) and six outputs (displacements). To achieve high-precision positioning capability, discrete-time integrator-augmented linear-quadratic-regulator (LQR) and reduced-order linearquadratic-Gaussian (LQG) control methodologies are applied. Digital multivariable controllers are designed and implemented on the positioning system, and experimental results are also presented in this paper to demonstrate the stage's dynamic performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.3
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• pp.58-66
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• 2012

This paper describes a design and a verification of linear state observers for a motorized seat belt system to estimate state information such as angular velocity and load torque. The motorized seat belt system provides functions to protect passengers and improve passenger's convenience. To realize these functions, sensors which can measure an angular velocity and load torque are needed. By use of the linear state observer, state information can be estimated without sensors. The motorized seat belt system is analysed and represented as a state space model which contains load torque as an augmented state. By the developed state space model, a full and reduced order observer are designed and verified by experiments. The full and reduced order observer are also compared from points of view of execution time and noise robustness.